There is little research on the needs or characteristics of children whose families are living doubled up with others or staying in temporary accommodations such as hotels, except for counts of school-age children provided by SEAs and LEAs and the study by Obradovic and colleagues (2009) described above. The NCHE (2009) provides some additional data about children in jurisdictions served by LEAs with ED McKinney-Vento Education for Homeless Children and Youth Program subgrants to provide additional services, but does not distinguish between the different definitions of homelessness for this purpose. Of 472,000 homeless school-age children served by subgrants, approximately 13 percent were reported to have limited English proficiency, 14 percent were reported to have unspecified disabilities, and fewer than 2 percent were from migratory families. Only 189,000 children (two fifths of those served by subgrants) were tested in reading and mathematics. Of these, 43 percent were judged proficient by state standards in reading and 42 percent in math. High school students were much less likely to meet proficiency standards (35 percent reading, 29 percent math) than younger children. The report contains no comparison data for other poor children, so it is hard to judge the relative progress of children who experience homelessness. The most mobile children were probably the least likely to be tested, but it is difficult to know the extent of the bias.

Although there is little direct data on children whose families are living doubled up or who are staying in hotels, there is a larger body of research on conditions to which these children are especially likely to be exposed, including extreme poverty, financial setbacks such as parental job loss, violence, residential mobility, school mobility, crowding, hunger, and other conditions recently summarized under the rubric of chaos (Evans & Wachs, 2010). This report considers each of these risk factors in turn and attempts to determine whether they are causally related to the poor outcomes with which they are associated or whether they simply serve as markers for poverty for which the adverse causal impact on children has been clearly demonstrated. Several researchers comparing children in shelter with poor domiciled children have found that a variety of risk factors are more important in predicting children’s outcomes than residential status per se (Buckner, Bassuk, Weinreb, & Brooks, 1999; Buckner, Beardslee, & Bassuk, 2004; Masten et al., 1993; Shinn et al., 2008). Thus this report discusses cumulative risk and also factors associated with children’s resilience. The review is necessarily selective, relying on other published review articles where they are available.

A large body of research summarized by McLoyd (1998) links poverty to adverse outcomes for children in the areas of health, cognitive development, academic achievement, and socio-emotional or mental health outcomes. Increasingly sophisticated research designs control for background characteristics of families that might lead both to poverty and to adverse outcomes for children. These include longitudinal designs that follow children over extended periods of time so that the effects of income loss can be examined for children, controlling for more stable background characteristics, as well as comparisons of siblings who experience different economic environments growing up.

It is also possible to examine the associations of outcomes, such as poor achievement, with poverty experienced by children either before or after the outcome is measured. If poverty causes the outcome, then poverty experienced by children before the outcome is measured should have a larger association than poverty measured later. If the association of the outcome with poverty measured earlier is comparable to the association with poverty measured later, then the relationship is not likely to be causal. Under these circumstances, it is more likely that stable background characteristics explain both exposure to poverty and the poor outcome. Family income has stronger effects on children’s cognitive development and school achievement than on socio-emotional functioning, whereas social class, typically assessed by parental education and occupation, is more strongly associated with socio-emotional problems, especially externalizing symptoms. Studies suggest that the timing of poverty is unrelated to cognitive or socio-emotional functioning, but that poverty in the preschool years reduces ultimate educational attainment more than poverty experienced later. The effects of income on children’s outcomes are nonlinear; that is, additional income makes more difference for children at or near poverty than for children higher in the income distribution (McLoyd, 1998).

Poverty can have adverse effects on children's health, developmental status, mental health and behavior through various mechanisms or intervening variables. Several of the mechanisms by which poverty exerts its detrimental effects are particularly relevant to the situation of homeless children. Cognitive stimulation in the home environment, such as the presence of books and of toys that teach color, size, or shape, is important to cognitive development. Both loss of income and duration of poverty predict declines in the quality of the home environment and declines in children’s IQ. Poor nutrition, exposure to legal and illegal drugs prenatally, and exposure to lead in poorly maintained older housing can lead to poor health or impairment of neurological functioning. Teachers may perceive students who are poor and of low socio-economic status less positively and thus expect less of them, give them less positive attention, offer fewer learning opportunities, and provide them with less positive reinforcement when they do well. Economic stressors may lead to parental depression or harsh or inconsistent parenting, which are associated with socio-emotional problems in children. Poor children are exposed to more chronic stressors — from family conflict to overcrowding — and also to more stressful life events than non-poor peers. Their self-esteem may be eroded by circumstances such as living in poor housing or bad neighborhoods that mark their membership in a stigmatized group (McLoyd, 1998). Each of these mechanisms seems likely to be in play for homeless children living in doubled-up situations, although perhaps not to the same extent as for children living in shelter or without shelter or in hotels or motels. The effects of stigma associated with homelessness may go beyond the effects of material deprivation. Nutrition and crowding are considered in more detail below.

Across multiple outcomes, including intelligence, school achievement, and socio-emotional functioning, persistent poverty has more detrimental effects than transitory poverty (Bolger et al., 1995; Duncan, Brooks-Gunn, Klebanov, 1994; McLoyd, 1998). Thus children from families that have always been poor are likely to be worse off than children in families that experience sudden hardship due, for example, to the recession and foreclosure crisis. However, sudden hardship also takes its toll. Conger and colleagues (1994) studied the effects on children and families of the dramatic economic decline in the rural Midwest in the 1980s, when thousands of farmers and small-town businessmen went bankrupt. In a sample of 378 seventh graders living in two-parent middle class families (mean income of $33,800 in 1988 dollars, mean education of 13.8 years), they found that economic pressures experienced by parents led to parental mood changes and marital conflict, along with conflict with children about money. These, in turn, led to greater general hostility of parents toward children and to adolescent emotional and behavioral problems.

Using data from the Panel Study in Income Dynamics, which followed a nationally representative sample of 5,000 families, Yeung and Hofferth (1998) examined instances where families had income reductions of 50 percent or more (which transpired for 894 families). Families who experienced a major income loss were more likely to move within the following year. The researchers found that higher income White families were more likely to reduce food expenditures when experiencing work reduction than lower income White families, but the opposite was true for Black families. Families who started with higher incomes were less likely over time to receive public assistance such as food stamps and TANF.

A recent paper from the National Bureau of Economic Research (Stevens & Schaller, 2009) examined data from the Survey of Income and Program Participation (SIPP) from 1996 to 2006. The authors looked at the relationship between parental job loss and children’s academic difficulties. The data include a series of panel datasets covering between 14,000 and 46,000 households per panel, each of which were followed for two to four years. This study shows that when a parent loses his or her job, the probability that a child will repeat a grade in school increases by almost one percentage point a year, or about a 15 percent increase in the probability of grade retention. These results using recent data represent the short-term impact of job loss and may be indicative of the impact of the current rise in unemployment and job loss that has affected many children who fit the broad definition of homelessness. Also, a substantial body of literature shows that unemployment leads to depression among both people who lose jobs and their spouses (e.g., Howe, Levy, & Caplan, 2004; Vinokur, Price, & Caplan, 1996), and that depression among parents is associated with adverse outcomes for children (e.g., Downey & Coyne, 1990).

Residential moves feature prominently in inventories of stressful life events for adults and children alike. Although researchers caution that the context of moves and the extent to which they are freely chosen are important determinants of their impact (Stokols & Shumaker, 1982), moves among families experiencing homelessness are likely associated with evictions by landlords or by the primary tenants at a previous residence and other adverse events over which children typically exercise little control. Scanlon and Devine (2001) reviewed research on residential mobility and found clear adverse effects on academic performance, rates of grade retention, and rates of high school graduation. At that time they judged the literature on behavioral outcomes to be too sparse to draw firm conclusions.

A more recent review of the relationship of residential moves to health, broadly construed, found high rates of residential mobility were associated with increased behavioral problems in both children and adolescents (Jellyman & Spencer, 2008). Children who moved more often exhibited more indirect aggression, committed more property offenses, and had more behavioral problems requiring psychological help. Adolescents had higher rates or earlier instances of drug use, depression, sexual behavior, and teen pregnancy. Families had less continuity in health care. Other studies (summarized by Hertzman, 2010) have found residential instability to be associated with lower school readiness and early behavioral and emotional problems for younger children.

For obvious reasons, families are never randomly assigned to high versus low mobility conditions to examine the effects, so an important concern in this literature is the extent to which mobility is simply a marker for poverty and other risk factors or is itself a causal variable. It is clear, for example, that low-income children move more often than their middle-income peers (e.g., Evans, Eckenrode, & Marcynyszyn, 2010). Jellyman and Spencer (2008) consider this caution, but find that effects of mobility hold after controlling for confounding variables. They suggest that mobility may be one way in which poverty exerts its effects on child outcomes.

School mobility is, of course, related to residential mobility and thereby difficult to tease apart. Like residential mobility, school mobility is associated with poverty (e.g., Evans et al., 2010). Studies consistently find that school mobility is associated with lower academic achievement when there are no controls for achievement prior to the moves. However, the small number of studies where achievement is measured during (Buckner, Bassuk, & Weinreb, 2001), or both

before and after the onset of mobility (e.g., Heinlein & Shinn, 2000), do not show clear effects of mobility between the two waves of data collection. Thus, school mobility, like residential mobility, may be more of a marker of a constellation of adverse conditions rather than an independent cause of poor outcomes. Nonetheless, stable schooling may serve as an anchor for children who experience other forms of instability.

Homeless children may be more likely than other children to experience school mobility in the midst of a school year, when they are confronted with new curricular demands as well as a new set of peers and teachers. Thus it is plausible that midyear moves are more problematic than moves over the summer. The McKinney-Vento Homeless Assistance Act requires that homeless children be allowed to stay in their school of origin if that is in the child’s best interest, and that school districts provide transportation to that school if requested by the child’s parent or guardian. Nevertheless, LEAs continue to report that transportation is the top barrier to access to education for homeless children (NCHE, 2009).

Homeless children living doubled up or in motels and hotels, like homeless children in shelters, often experience high levels of crowding, typically indexed by the number of people per room. Residential crowding, across a number of studies reviewed by Evans (2006), has been associated with social withdrawal, elevated levels of aggression, psychological distress, poor behavioral adjustment in school, and lower levels of social and cognitive competency. Parents in crowded homes talk less to infants, are less responsive to young children, and are more likely to engage in punitive parenting than other parents. Crowding effects appear in studies with good controls for socio-economic status and in laboratory and field experiments.

According to a U.S. Department of Agriculture survey (Nord, 2009), 15.8 percent of households with children were food insecure at some time during 2007. In many of those households, parents were able to protect children from food insecurity, but in 8.3 percent of these households, children too were food insecure, typically due to reductions in the quality and variety of meals. In 0.8 percent of households, children had very low food security: they had been hungry when the household could not afford food, skipped a meal, or did not eat for an entire day because of lack of money for food. Food insecurity is associated with poorer health, higher hospitalization levels, more behavioral and emotional problems, and lower cognitive achievement and achievement gains. Food insecurity is higher in households with some characteristics that are common among homeless families, such as African American race; single female-headed households; and incomes below the poverty line, although more than two thirds of families with food insecurity among children had at least one full-time worker (Nord, 2009).

Poor nutrition appears to be a cause of poor child outcomes and not simply a marker of other conditions. In multiple experimental studies, most in other nations, provision of nutritional supplements to pregnant mothers and to infants improved children’s developmental outcomes. Longer term supplementation during pregnancy and early childhood had positive effects on adolescent cognitive development 12 years after the supplements were discontinued. Temporary food shortages affected social involvement and classroom attentiveness during a drought in Kenya and mathematics skills assessed several years later (Sigman, 1995).

Weinreb and colleagues (2002) examined hunger and its impact on child health and mental health in a sample of homeless and low-income housed children (some of whom would meet the ED definition of homeless) ages 2–18 in Worcester, MA. Among preschool age children in both groups, 51 percent experienced moderate hunger and 8 percent experienced severe hunger. Severe hunger was more common among homeless children and was associated with high levels of chronic illness and internalizing behavior problems. More school-age children in the housed group experienced hunger than did homeless children. Severe hunger among school-age children was linked to chronic illness and symptoms of anxiety and depression.

Researchers often attempt to single out the unique effects of particular stressors on various aspects of children’s well-being. However, there exist many different types of negative events that children living in poverty can experience, making it difficult to examine their effects individually. Moreover, the conditions just described often co-occur in the lives of homeless children. Masten and colleagues (1993) described the count of significant negative life events a child has dealt with as cumulative risk. Researchers have typically found that such counts are more predictive of children’s outcomes than homelessness per se. This is not surprising as indices of cumulative risk capture a much broader array of adversities that children living in poverty can experience than just homelessness per se. Similarly, Buckner, Beardslee, and Bassuk (2004), who followed up families after they were re-housed, found that negative life events, particularly exposure to violence in the home and the community, were more important to children’s mental health than prior homelessness. This is not to argue that the effects of homelessness on children are inconsequential. However, it is important to remember that homelessness is but one of many major adversities that children living in poverty can experience and is often time limited. Living in a dangerous neighborhood and intermittently witnessing or being the victim of violence can be an even more chronic stressor than homelessness and can have more enduring effects on children's social-emotional functioning.

Finally, Shinn and colleagues (2008), who examined formerly homeless and continuously housed children five years after the former group entered shelter, found recent life events and proximal stressors reported by the mother (current economic stressors, current maternal depressive symptoms, perceived lack of safety in the current neighborhood) were more important than distal stressors (over the past five years or in the last year) or prior homelessness to children’s mental health.

Wachs and Evans (2010) conceptualize all of the conditions described here and other forms of instability as manifestations of chaos, having a profound effect on children’s lives. Just as lack of stimulation can impede development, unpredictable and uncontrollable settings may have adverse physiological consequences, interfere with children’s self-regulation and sense of efficacy, impair the quality of parenting they receive, and impede their ability to regulate external demands and acquire a sense of order and continuity.

While it would be a mistake to assume that the lives of most homeless families in America are chaotic, it can be difficult for parents to provide stability and routines for their children without a secure residence. Families who double up with others; live in hotels, motels, or shelters; or live in campgrounds, vehicles, or other places not designed for human habitation must struggle to provide a sense of stability and security for their children. Homeless families living doubled up with others live in a more normalized setting, but it cannot be assumed they are at lower risk without research. Homeless families living in shelter at least have the advantage of being better linked to the social service system than families living doubled up in the community.

Resilience in children has been defined as "achieving desirable outcomes in spite of significant challenges to adaptation or development" (Masten & Coatsworth, 1995, p.737). The prerequisite for evidencing resilience is to have faced a major adversity of some sort. Of the many published studies of resilience involving children and adolescents, relatively few have examined children's resilience in the context of poverty.

Buckner, Mezzacappa, and Beardslee (2003) conducted a study comparing 45 resilient to 70 non-resilient youths from extremely low-income families in Worcester, Massachusetts. A third of these school-age children had been homeless within the past two years and all were from households with incomes below the poverty line. Hence this study has applicability to children meeting the HUD and ED definitions of homelessness. Resilience was operationally defined in a multidimensional manner using well-established instruments that measured children's emotional well-being, behavior, competence, and level of functioning. Children deemed resilient showed positive adjustment in each of these realms, whereas those determined to be non-resilient evidenced significant problems in one or more of these areas. Although participants in this study all lived below the poverty line, there was still substantial variation in the quantity of negative events and chronic stressors they had experienced in recent years. Because these adversities were predictive of outcomes in expected directions, it was necessary to statistically control for them in order to better understand the independent contributions of inner and external resources to predicting resilience.

While this study was limited to a cross-sectional comparison of children, a decided strength was its extensive assessment battery, which comprised data collected directly from the child as well as from a parent and an external rater. In combination with multivariate analyses, this allowed the investigators to examine the relative contribution of an array of variables, reflecting both inner and external resources of a child, in predicting their resilience status. Among inner resources, self-esteem and, especially, self-regulation skills emerged as independent predictors of resilience. Likewise, among external resources that were examined, parental monitoring stood out as a predictor, controlling for all other explanatory variables. The parental monitoring variable tapped into a parent's proclivity to pay close attention to the whereabouts of a child when away from home and with whom the child was spending time. Of note, the nonverbal intelligence of a child, while associated with resilience status in some analyses, was not a predictor of resilience status in multivariate modeling. Instead, self-regulation (which was positively associated with intelligence) was the much more potent predictor.

Similarly, Obradovic (2010) examined the relationship between effortful control, assessed in laboratory tasks such as the ability to play “Simon Says,” and adaptive functioning for 58 homeless children who were entering kindergarten or first grade and were sampled in shelter. Effortful control, a skill closely related to self-regulation, was strongly related to all four measures of adaptive functioning rated by teachers (academic functioning, peer competence, low levels of internalizing behaviors, and low levels of externalizing behaviors), controlling for IQ, parenting quality, and risk levels. Further, age and effortful control were the only predictors of resilience, defined as showing adaptive behavior across all four domains.

Both theory and recent empirical findings are supportive of the argument that self-regulation skills may be an important inner resource for children, including those who are currently homeless or otherwise living in poverty (Buckner, Mezzacappa, & Beardslee, 2009). Self-regulation refers to an integrated set of meta-cognitive skills that draw from both executive function and emotion regulation capacities, which are invoked in the service of accomplishing both proximal and distal goals. While associated with intelligence, self-regulation is a somewhat separate construct that may have closer links to adaptive functioning in children and adults. An appeal of self-regulation is that it can be conceived as a set of skills that can be improved through intervention. (e.g., Diamond, Barnett, Thomas, & Munro, 2007).

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